Table of Contents
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Job Overview
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About the Company
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Available Jobs
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Job Description
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Job Responsibilities
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Why This Role?
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Requirements
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How to Apply
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FAQs
Job Overview
Job Title: Data Engineer
Company Name: Keystone AI
Location: Dubai, United Arab Emirates
Employment Type: Full-time
Start Date: ASAP (role is actively hiring)
Salary: Competitive (with annual discretionary bonus, pension contribution, and benefits; compensation varies by level and experience)
Opportunity Summary:
As a Data Engineer in Dubai, you will design, build, and optimize data systems that power Keystone AI’s high-impact analytical and forensic engagements. This role blends deep technical execution with strategic consulting outcomes—building reproducible pipelines, secure cloud infrastructure, and AI-enabled workflows that turn complex datasets into defensible insights for regulated sectors across the MENA region and beyond.
About the Company
Keystone AI is a tech-forward strategy and economics consulting firm with more than two decades of experience helping leading technology companies, global brands, and top law firms solve complex challenges in competition, strategy, and regulation. Their model brings together what they call a “Triad of Skills”—economics, strategy, and technology—to deliver digital transformation and business model innovation with real-world impact.
The firm’s work spans high-stakes engagements where the quality of analysis, the reliability of the data, and the defensibility of methods matter. Keystone’s Economic, Technology, and Strategy Advisory (ETSA) group supports legal and regulatory matters and builds rigorous reports and technology solutions that influence decisions at scale. In practical terms: your engineering work won’t sit in a backlog—it will be part of the evidence and insight engine that helps clients win.
Available Jobs
If you’re exploring Keystone AI and want to widen your keyword coverage (or find a role that matches your strongest edge), here are closely related roles you can also look for:
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Senior Data Engineer – Cloud & AI Enablement (Dubai)
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Machine Learning Engineer – LLM Systems and Evaluation
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Analytics Engineer – dbt, Warehousing, and Governance
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Data Scientist – Forensic and Regulatory Analytics
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Software Engineer – APIs, Data Platforms, and Automation
These titles align with the same toolkit: cloud platforms, SQL + Python, orchestration, scalable data processing, and AI/LLM integration.
Job Description
This Data Engineer Dubai role is designed for someone who can bridge technical innovation and strategic insight. You’ll partner with consultants and investigators to architect secure, high-performance data infrastructure across cloud environments, then build reproducible ingestion pipelines and analytical workflows that hold up under scrutiny—especially important in regulated sectors, investigations, and legal contexts.
Unlike typical “move data from A to B” positions, this role also includes building custom software and APIs, integrating LLMs, supporting digital investigations, and enabling AI/ML-driven analysis (including vector databases and retrieval-augmented generation systems). If you’ve been looking for a role where data engineering directly influences decision-making at the highest levels, this is that lane.
Job Responsibilities
In this position, you will:
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Partner with consultants and investigators to architect secure, high-performance data infrastructure across cloud environments.
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Build reproducible data ingestion pipelines and analytical workflows that transform raw data into strategic, client-ready insights.
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Develop custom software tools and APIs to automate data discovery, integrate large language models (LLMs), and support digital investigations.
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Leverage modern ETL/ELT practices, advanced SQL, and big data technologies to process diverse and complex datasets efficiently.
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Implement tools and libraries that increase scalability, auditability, and delivery efficiency—especially for technical investigations.
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Support AI/ML-driven analysis, including:
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model fine-tuning and evaluation
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deployment support
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vector databases and RAG (retrieval-augmented generation) systems
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Provide input on data governance, cybersecurity, and compliance standards relevant to the MENA region.
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Collaborate cross-functionally with data science, forensic analysis, and regulatory strategy teams to deliver innovative client outcomes.
Why This Role?
Keystone AI’s Data Engineer opening stands out for engineers who want their work to matter in ways that go beyond product metrics.
Work that’s defensible, not just scalable
In many roles, “done” means the pipeline runs. Here, “done” often means the methodology is auditable, explainable, and defensible—a rare and valuable skillset, especially as AI and data face increasing regulatory scrutiny.
AI + data engineering is central, not optional
This isn’t an environment where LLMs are a side experiment. You’ll build systems that integrate modern AI workflows—vector search, RAG pipelines, evaluation loops—while still meeting the reliability and security expectations of regulated work.
Exposure to frontier domains
You’ll work on matters shaping the future of AI, data, and digital regulation, often with multidisciplinary teams spanning economics, technology, and strategy. That combination can accelerate your growth into roles like Lead Data Engineer, AI Platform Engineer, or Analytics Architecture.
Consulting pace with engineering craftsmanship
If you like variety, this role gives you multiple problem types—data discovery, ingestion, modeling, automation, governance, and secure delivery—without sacrificing engineering quality.
Strong total rewards (competitive)
Compensation is positioned as competitive, with bonus potential, pension contribution, and benefits—structured around level and experience.
Requirements
Below is what Keystone AI is looking for, summarized in a practical way.
Experience
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Proven experience in data engineering, data science, or ETL/ELT workflows with large, complex datasets
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Comfortable operating in a dynamic environment across cultures and time zones
Cloud & Data Platforms
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Proficiency with at least one major cloud platform: AWS, GCP, or Azure
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Familiarity with cloud data services (examples mentioned include Lambda and AI services like Bedrock or Vertex AI)
Programming & Querying
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Advanced working knowledge of Python and SQL for data manipulation and analysis
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Working knowledge of R is a plus (especially for analytical workflows)
Orchestration & Big Data Ecosystems
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Familiarity with orchestration tools such as Airflow, dbt, Prefect, or Luigi
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Familiarity with big data / warehouse platforms such as Snowflake, Spark, or BigQuery
AI/ML & LLM-Adjacent Skills
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Exposure to AI/ML/NLP concepts and production implementation
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Hands-on experience with ML libraries/frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and/or the OpenAI API
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Experience supporting vector databases and RAG-style systems is a strong advantage
Engineering Fundamentals
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Understanding of SDLC principles, Git, and CI/CD pipelines
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Ability to build scalable solutions with strong reliability, monitoring, and documentation practices
Education
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Bachelor’s degree in Computer Science, Data Engineering, or related field (Master’s preferred)
Advantage Areas
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Experience or interest in digital investigations, compliance analytics, or forensic data work
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Comfort working in regulated, high-stakes contexts where governance and security matter
How to Apply
Apply directly through Keystone AI’s career page and submit your application for the Data Engineer – Dubai position.
FAQs (Frequently Asked Questions)
1) Is this a full-time on-site job in Dubai?
The role is listed in Dubai and presented as a standard full-time position. If you need flexibility, it’s best to address work style expectations during the interview process.
2) Do I need AWS specifically to apply?
Not necessarily. Keystone AI notes proficiency with AWS, GCP, or Azure. Strong cloud data engineering fundamentals matter most, and you can adapt services across platforms.
3) Is AI/LLM experience required for this Data Engineer Dubai role?
You don’t need to be an ML researcher, but AI/ML/NLP exposure and comfort supporting production AI workflows is important—especially around LLM integration, vector databases, and RAG systems.
4) What kind of projects will I work on?
You’ll support analytical and forensic engagements, building data infrastructure, ingestion pipelines, APIs, and scalable systems that support investigations, compliance analytics, and regulated-sector insight delivery.
5) Is the salary disclosed?
The listing describes compensation as competitive, with a discretionary bonus, pension contribution, and benefits. Final compensation depends on your level, skills, and experience.